Information Asymmetry and Insurance in Africa

ABSTRACT

In this study, we assess the relevance of decreasing information asymmetry on life and non-life insurance consumption, by using data from 48 African countries during the period 2004–2014. Reduced information asymmetry is proxied by information sharing offices, namely: public credit registries and private credit bureaus. The empirical evidence is based on the Generalized Method of Moments. The findings show that information sharing offices increase insurance consumption with a comparatively higher magnitude in life insurance penetration, relative to non-life insurance penetration. Practical and theoretical implications are discussed.

KEYWORDS:

• Insurance
• information asymmetry

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ The 48 countries include: Algeria, Angola, Benin, Botswana, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo Democratic Republic, Congo Republic, Côte d’Ivoire, Djibouti, Egypt, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome & Principe, Senegal, Seychelles, Sierra Leone, South Africa, Sudan, Swaziland, Tanzania, Togo, Tunisia, Uganda and Zambia.

² Hence, the procedure for treating ivstyle (years) is ‘iv (years, eq(diff))’ whereas the gmmstyle is employed for predetermined variables.

³ “eq(diff)” stands for equation in difference.

⁴ “First, the null hypothesis of the second-order Arellano and Bond autocorrelation test (AR (2)) in difference for the absence of autocorrelation in the residuals should not be rejected. Second the Sargan and Hansen over-identification restrictions (OIR) tests should not be significant because their null hypotheses are the positions that instruments are valid or not correlated with the error terms. In essence, while the Sargan OIR test is not robust but not weakened by instruments, the Hansen OIR is robust but weakened by instruments. In order to restrict identification or limit the proliferation of instruments, we have ensured that instruments are lower than the number of cross-sections in most specifications. Third, the Difference in Hansen Test (DHT) for exogeneity of instruments is also employed to assess the validity of results from the Hansen OIR test. Fourth, a Fisher test for the joint validity of estimated coefficients is also provided” (Asongu & De Moor, 2017, p. 200).